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arXiv 2024年

作者： Yeguas-Bolívar, Enrique Alcalde-Llergo, José M. Aparicio-Martínez, Pilar Taborri, Juri Zingoni, Andrea Pinzi, Sara Computing and Numerical Analysis University of Córdoba Córdoba Spain University of Córdoba Córdoba Spain Nursing Physiotherapy and Pharmacology University of Córdoba Córdoba Spain University of Tuscia Viterbo Italy Dept. Physical Chemistry and Applied Thermodynamics University of Córdoba Córdoba Spain

Learning disorders are neurological conditions that affect the brain’s ability to interconnect communication areas. Dyslexic students experience problems with reading, memorizing, and exposing concepts;however the magnitude of these can be mitigated through both therapies and the creation of compensatory mechanisms. Several efforts have been made to mitigate these issues, leading to the creation of digital resources for students with specific learning disorders attending primary and secondary education levels. Conversely, a standard approach is still missed in higher education. The VRAIlexia project has been created to tackle this issue by proposing two different tools: a mobile application integrating virtual reality (VR) to collect data quickly and easily, and an artificial intelligence-based software (AI) to analyze the collected data for customizing the supporting methodology for each student. The first one has been created and is being distributed among dyslexic students in Higher Education Institutions, for the conduction of specific psychological and psychometric tests. The second tool applies specific artificial intelligence algorithms to the data gathered via the application and other surveys. These AI techniques have allowed us to identify the most relevant difficulties faced by the students’ cohort. Our different models have obtained around 90% mean accuracy for predicting the support tools and learning strategies. © 2024, CC BY.

关键词： Students

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A VR Serious Game to Increase Empathy Towards Students with Phonological Dyslexia

A VR Serious Game to Increase Empathy Towards Students with ...

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Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), IEEE International Conference on

作者： José M. Alcalde-Llergo Enrique Yeguas-Bolívar Pilar Aparicio-Martínez Andrea Zingoni Juri Taborri Sara Pinzi Dept. of Economics Engineering Society and Business Organization (DEIM) University of Tuscia Viterbo Italy Computing and Numerical Analysis University of Córdoba Córdoba Spain Nursing Physiotherapy and Pharmacology University of Córdoba Córdoba Spain Dept. Physical Chemistry and Applied Thermodynamics University of Córdoba Córdoba Spain

Dyslexia is a neurodevelopmental disorder that is estimated to affect about 5-10% of the population. In particular, phonological dyslexia causes problems in connecting the sounds of words with their written forms. This results in difficulties such as slow reading speed, inaccurate reading, and difficulty decoding unfamiliar words. Moreover, dyslexia can also be a challenging and frustrating experience for students as they may feel misunderstood or stigmatized by their peers or educators. For these reasons, the use of compensatory tools and strategies is of crucial importance for dyslexic students to have the same opportunities as non-dyslexic ones. However, generally, people underestimate the problem and are not aware of the importance of support methodologies. In the light of this, the main purpose of this paper is to propose a virtual reality (VR) serious game through which teachers, students and, in general, non-dyslexic people could understand which are some of the issues of student with dyslexia and the fundamental utility of offering support to them. In the game, players must create a potion by following a recipe written in an alphabet that is specifically designed to replicate the reading difficulties experienced by individuals with dyslexia. The task must be solved first without any help and then by receiving supporting tools and strategies with the idea that the player can put himself in the place of the dyslexic person and understand the real need for support methodologies.

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Brain solute transport is more rapid in periarterial than perivenous spaces

Research Square

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Research Square 2021年

作者： Vinje, Vegard Bakker, Erik Nicolaas Theodorus Petrus Rognes, Marie E. Department of Scientific Computing and Numerical Analysis Simula Research Laboratory Martin Linges vei 25 Fornebu 1364 Norway Amsterdam University Medical Center Dept. of Biomedical Engineering and Physics Meibergdreef 9 Amsterdam1105 AZ Netherlands University of Bergen Department of Mathematics Bergen Norway

Background: Perivascular fluid flow, of cerebrospinal or interstitial fluid in spaces surrounding brain blood vessels, is recognized as a key component underlying brain transport and clearance. An important open question is how and to what extent differences in vessel type or geometry affect perivascular fluid flow and transport. Methods: Using computational modelling in both idealized and image-based geometries, we study and compare fluid flow and solute transport in pial (surface) periarterial and perivenous spaces. Results: Our findings demonstrate that differences in geometry between arterial and venous pial perivascular spaces (PVSs) lead to higher net CSF flow, more rapid tracer transport and earlier arrival times of injected tracers in periarterial spaces compared to perivenous spaces. Conclusions: These findings can explain the experimentally observed rapid appearance of tracers around arteries, and the delayed appearance around veins without the need of a circulation through the parenchyma, but rather by direct transport along the PVSs. © 2021, CC BY.

关键词： Blood vessels

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Time series ordinal classification via shapelets

Time series ordinal classification via shapelets

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International Joint Conference on Neural Networks (IJCNN)

作者： David Guijo-Rubio Pedro A. Gutiérrez Anthony Bagnall César Hervás-Martínez Dept. of Computer Science and Numerical Analysis University of Córdoba Córdoba Spain School of Computing Sciences University of East Anglia Norwich United Kingdom

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Nominal time series classification has been widely developed over the last years. However, to the best of our knowledge, ordinal classification of time series is an unexplored field, and this paper proposes a first approach in the context of the shapelet transform (ST). For those time series dataset where there is a natural order between the labels and the number of classes is higher than 2, nominal classifiers are not capable of achieving the best results, because the models impose the same cost of misclassification to all the errors, regardless the difference between the predicted and the ground-truth. In this sense, we consider four different evaluation metrics to do so, three of them of an ordinal nature. The first one is the widely known Information Gain (IG), proved to be very competitive for ST methods, whereas the remaining three measures try to boost the order information by refining the quality measure. These three measures are a reformulation of the Fisher score, the Spearman's correlation coefficient (ρ), and finally, the Pearson's correlation coefficient (R 2 ). An empirical evaluation is carried out, considering 7 ordinal datasets from the UEA & UCR time series classification repository, 4 classifiers (2 of them of nominal nature, whereas the other 2 are of ordinal nature) and 2 performance measures (correct classification rate, CCR, and average mean absolute error, AMAE). The results show that, for both performance metrics, the ST quality metric based on R 2 is able to obtain the best results, specially for AMAE, for which the differences are statistically significant in favour of R 2 .

关键词： Time series analysis Shape measurement Time measurement Correlation Computer science numerical analysis

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Preconditioned smoothers for the full approximation scheme for the RANS equations

arXiv

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arXiv 2017年

作者： Birken, Philipp Bull, Jonathan Jameson, Antony Centre for the Mathematical Sciences Numerical Analysis Lund University Lund Sweden Division of Scientific Computing Dept. of Information Technology Uppsala University Box 337 Uppsala75105 Sweden Stanford University Department of Aeronautics and Astronautics StanfordCA94305 United States

We consider multigrid methods for finite volume discretizations of the Reynolds Averaged Navier-Stokes (RANS) equations for both steady and unsteady flows. We analyze the effect of different smoothers based on pseudo time iterations, such as explicit and additive Runge-Kutta (ARK) methods. Furthermore, we derive the new class of additive W (AW) methods from Rosenbrock smoothers. This gives rise to two classes of preconditioned smoothers, preconditioned ARK and additive W (AW), which are implemented the exact same way, but have different parameters and properties. The new derivation allows to choose some of these based on results for time integration methods. As preconditioners, we consider SGS preconditioners based on flux vector splitting discretizations with a cutoff function for small eigenvalues. We compare these methods based on a discrete Fourier analysis. numerical results on pitching and plunging airfoils identify AW3 as the best smoother regarding overall efficiency. Specifically, for the NACA 64A010 airfoil steady-state convergence rates of as low as 0.85 were achieved, or a reduction of 6 orders of magnitude in approximately 25 pseudo-time iterations. Unsteady convergence rates of as low as 0.77 were achieved, or a reduction of 11 orders of magnitude in approximately 70 pseudo-time iterations. Copyright © 2017, The Authors. All rights reserved.

关键词： Runge Kutta methods

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A STUDY of multigrid smoothers used in compressible CFD based on the convection diffusion equation 7

A STUDY of multigrid smoothers used in compressible CFD base...

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7th European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS Congress 2016

作者： Birken, Philipp Bull, Jonathan Jameson, Antony Lund University Centre for the Mathematical Sciences Numerical Analysis Box 118 Lund22100 Sweden Uppsala University Division of Scientific Computing Dept. of Information Technology Box 337 Uppsala75105 Sweden Stanford University Department of Aeronautics and Astronautics StanfordCA94305 United States

ISBN: (纸本)9786188284401

We look at multigrid methods for unsteady viscous compressible flows. We specifically target smoothers that can be used in parallel and without computation of a Jacobian, which are particlarly attractive candidates in the context of Discontinuous Galerkin discretizations. In CFD, a plethora of nonlinear smoothers have been suggested which are hard to analyze. Our methodology is to use a linear model problem, here the convection diffusion equation, to be able to classify and compare smoothers better. Specifically, we consider explicit and implicit pseudo time iterations, GMRES as a smoother, SGS and implicit line smoothers. We relate GMRES to explicit Runge-Kutta smoothers, identify implicit line smoothers as Block Jacobi and analyze the potential of implicit pseudo time iterations. Finally, we discuss the relation between methods for steady and unsteady flows. numerical results show that GMRES is a very attractive smoother in this context.

关键词： Unsteady flow

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A note on terminology in multigrid methods

A note on terminology in multigrid methods

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Joint 87th Annual Meeting on the International Association of Applied Mathematics and Mechanics, GAMM 2016 and Deutsche Mathematiker‐Vereinigung, DMV 2016

We compare terminology used in the literature on multigrid methods for compressible computational fluid dynamics to that used in linear multigrid theory. Several popular iterative and direct smoothers are presented side-by-side using the same terminology. We argue for greater analysis of these methods in order to place them into a more rigorous framework and to identify the most promising candidates for future development. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

关键词： Terminology

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A note on terminology in multigrid methods

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PAMM 2016年第1期16卷

作者： Philipp Birken Jonathan Bull Antony Jameson Lund University Centre for the Mathematical Sciences Numerical Analysis Box 118 22100 Lund Uppsala University Division of Scientific Computing Dept. of Information Technology Box 337 75105 Uppsala Stanford University Department of Aeronautics & Astronautics Stanford CA 94305

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The firefighter problem: Application of hybrid ant colony optimization algorithms 14

The firefighter problem: Application of hybrid ant colony op...

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14th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2014

作者： Blum, Christian Blesa, Maria J García-Martínez, Carlos Rodríguez, Francisco J. Lozano, Manuel Dept. of Computer Science and Artifical Intelligence Univ. of the Basque Country UPV/EHU San Sebastian Spain IKERBASQUE Basque Foundation for Science Bilbao Spain ALBCOM Research Group Univ. Politécnica de Catalunya Barcelona Spain Dept. of Computing and Numerical Analysis Univ. of Córdoba Spain Dept. of Computer Science and Artificial Intelligence Univ. of Granada Spain

ISBN: (纸本)9783662443194

The firefigther problem is a deterministic discrete-time model for the spread (and the containment) of fire on an undirected graph. Assuming that the fire breaks out at a predefined set of vertices, the goal is to save as many vertices as possible from burning. The same model has also been used in the literature for the simulation of the spreading of deseases. In this work we present, to our knowledge, the first metaheuristics for tackling this problem. In particular, a pure ant colony optimization approach and a hybrid variant of this algorithm are proposed. The results show that the hybrid ant colony optimization variant is superior to the pure ant colony optimization version and to a mathematical programming solver, especially when the graph size and density grows. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Ant colony optimization

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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